Abstract 4088: A novel real world clinico-genomics data platform identifies breast cancer histologic and molecular characteristics as candidate predictors for time to distant metastasis
Authors: Amanda Nottke, Anthony B. Cardillo, Hana E. Littleford, Lisandra West-Odell, Alexandra Berk
Journal: Cancer Research (2022)

Abstract Introduction: Currently, the NCCN guidelines for invasive breast cancer (BC) surveillance are the same regardless of tumor pathology. The length of time between initial diagnosis and documented distant metastasis based on tumor subtypes has not been well-studied in real-world settings, which means that for any given patient, generalized screening recommendations may be either too stringent or too relaxed. Here, we report how tumor histologic and molecular characteristics analyzed from a real-world data platform correlate with the average time to distant recurrence. This information can guide more personalized surveillance for BC patients. Methods: Ciitizen (a wholly owned subsidiary of Invitae) leverages HIPAA right of access on behalf of patients to collect their medical records, extracts relevant clinical information into a standardized and validated longitudinal dataset, and - with their consent - enables research use of this data. From our current invasive BC cohort (n=1011), we identified a subcohort who were diagnosed at Stage I-III with associated histology and/or molecular characterization, then ultimately went on to develop distant metastases (n=195 cases involving 321 sites: bone, brain, liver, and/or lung). We calculated time from initial diagnosis to confirmation of distant metastasis at each site, and statistically analyzed differences using pooled hypothesis testing. Results: In addition to finding expected associations between molecular type and site(s) of metastasis, i.e. bone and brain more common in Hormone Receptor Positive (HR+) subtypes vs HR-, we also characterized the average time to distant metastasis (TDM) to identify other statistically significant associations: Molecular Type: HR-/HER2- (n=30) has an average TDM of 1124 days, which is significantly faster than HR+/HER2- (2224 days; n=197) and HR+/HER2+ (2159 days; n=32) (p=0.0043). BRCA: Individuals with BRCA1/2 pathogenic germline variants have an average TDM of 1043 days (n=15), significantly earlier than individuals with normal BRCA1/2 (2238 days; n=179) (p &amp;lt;0.0001). Histology: Ductal carcinomas have an average TDM of 2262 days (n=242) and lobular carcinomas have an average TDM of 2812 days (n=24), both of which are significantly longer than the rarer metaplastic (739 days; n=11) and inflammatory (978 days; n=5) (p=0.0001). Conclusions: These real-world findings characterize average time to metastasis and reveal statistically significant associations based on histologic and molecular type, which taken together can inform more personalized screening recommendations for BC patients. Since the Ciitizen data platform also includes additional treatment and outcome variables, future studies can explore the relationships between these various features towards more granular prognostic and predictive classifications. Citation Format: Amanda Nottke, Anthony B. Cardillo, Hana E. Littleford, Lisandra West-Odell, Alexandra Berk. A novel real world clinico-genomics data platform identifies breast cancer histologic and molecular characteristics as candidate predictors for time to distant metastasis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 4088.